---
title: Versioning support in the Model Registry
description: Create registered models to provide an additional layer of organization to your model packages.
section_name: MLOps
maturity: public-preview

---

# Versioning support in the Model Registry {: #enable-versioning-support-in-the-model-registry }

!!! info "Availability information"
    Versioning support in the Model Registry is off by default. Contact your DataRobot representative or administrator for information on enabling this feature.

    <b>Feature flag:</b> Enable Versioning Support in the Model Registry

The Model Registry is an organizational hub for various models used in DataRobot, where you can access models as deployment-ready model packages. Now available for Public Preview, the **Model Registry > Registered Models** page provides an additional layer of organization to your models. 

![](images/reg-models-page.png)

On this page, you can group model packages into _registered models_, allowing you to categorize them based on the business problem they solve. Registered models can contain:

* DataRobot, custom, and external models

* Challenger models (alongside the champion)

* Automatically retrained models.

Once you add registered models and registered model versions, you can search, filter, and sort them. You can also share your registered models (and the versions they contain) with other users.

## Add registered models

You can register DataRobot, custom, and external model packages. When you add model packages to the **Registered Models** page, you can create a new registered model (version one) or save the model package as a new version of an existing registered model. Model packages added as versions of the same registered model _must_ have the same target type, target name, and, if applicable, target classes and time series settings.

Each registered model on the **Registered Models** page _must_ have a unique name. If you choose a name that exists anywhere within your organization when creating a new registered model, the **Model registration failed** warning appears. Use a different name or add this model as a new version of the existing registered model.

### Add a DataRobot model

To add a DataRobot model as a registered model or version:

1. Navigate to **Models > Leaderboard**.

2. From the **Leaderboard**, click the model you want to register and click **Predict > Deploy**.

3. Under **Deploy model**, click **Add to Model Registry**.

    ![](images/reg-dr-model.png)

4. In the **Register new model** dialog box, configure the following:

    ![](images/reg-model-fields.png)

    | Field | Description |
    |-------|-------------|
    | Register model | Select one of the following:<ul><li>**Register new model:** Create a new registered model. This creates the first version (**V1**).</li><li>**Save as a new version to existing model:** Create a version of an existing registered model. This increments the version number and adds a new version to the registered model.</li></ul> |
    | Registered model name / Registered Model | Do one of the following:<ul><li>**Registered model name:** Enter a unique and descriptive name for the new registered model. If you choose a name that exists anywhere within your organization, the **Model registration failed** warning appears.</li><li>**Registered Model:** Select the existing registered model you want to add a new version to.</li></ul> |
    | Registered model version | Assigned automatically. This displays the expected version number of the version (e.g., V1, V2, V3) you create. This is always **V1** when you select **Register a new model**. |
    | **Optional settings**  | :~~: | :~~: |
    | Version description | Describe the business problem these model packages solve, or, more generally, the relationship between them.            |
    | Tags | Click **+ Add item** and enter a **Key** and a **Value** for each key-value pair you want to tag the model _version_ with. Tags do not apply to the registered model, just the versions within. Tags added when registering a new model are applied to **V1**. |

5. Click **Add to registry**.

### Add a custom model

To add a custom model as a registered model or version:

1. Navigate to **Model Registry > Custom Model Workshop**.

2. From the **Custom Model Workshop**, click the model you want to register and, on the **Assemble** tab, click **Add to Model Registry**.

    ![](images/reg-cus-model.png)

4. In the **Register new model** dialog box, configure the following:

    ![](images/reg-model-fields.png)

    | Field | Description |
    |-------|-------------|
    | Register model | Select one of the following:<ul><li>**Register new model:** Create a new registered model. This creates the first version (**V1**).</li><li>**Save as a new version to existing model:** Create a version of an existing registered model. This increments the version number and adds a new version to the registered model.</li></ul> |
    | Registered model name / Registered Model | Do one of the following:<ul><li>**Registered model name:** Enter a unique and descriptive name for the new registered model. If you choose a name that exists anywhere within your organization, the **Model registration failed** warning appears.</li><li>**Registered Model:** Select the existing registered model you want to add a new version to.</li></ul> |
    | Registered model version | Assigned automatically. This displays the expected version number of the version (e.g., V1, V2, V3) you create. This is always **V1** when you select **Register a new model**. |
    | **Optional settings**  | :~~: |
    | Version description | Describe the business problem these model packages solve, or, more generally, the relationship between them.            |
    | Tags | Click **+ Add item** and enter a **Key** and a **Value** for each key-value pair you want to tag the model _version_ with. Tags do not apply to the registered model, just the versions within. Tags added when registering a new model are applied to **V1**. |

5. Click **Add to registry**.

### Add an external model

To add an external model as a registered model or version:

1. On the **Model Registry > Registered Models** page, click **Register New Model > External model**.

    ![](images/reg-ext-model.png)

2. In the **Register new external model** dialog box, configure the following:

    ![](images/ext-model-fields.png)

    | Field | Description |
    |-------|-------------|
    | Package Name | The name of the model package. |
    | Package description (optional) | Information to describe the model package. |
    | Model location (optional) |  The location of the model running outside of DataRobot. Describe the location as a filepath, such as folder1/opt/model.tar. |
    | Build Environment | The programming language in which the model was built. |
    | Training data (optional) |  The filename of the training data, uploaded locally or via the **AI Catalog**. Click **Clear selection** to upload and use a different file. |
    | Holdout data (optional) | The filename of the holdout data, uploaded locally or via the **AI Catalog**. Use holdout data to set an [accuracy baseline](#set-an-accuracy-baseline) and enable support for target drift and challenger models. |
    | Target | The dataset column name the model will predict on. |
    | Prediction type | The type of prediction the model is making, either binary classification or regression. For a classification model, you must also provide the positive and negative class labels and a prediction threshold. |
    | Prediction column | The column name in the holdout dataset containing the prediction result. |

    If registering a [time series](time/index) model, select the **This is a time series model** checkbox and configure the following fields:

    ![](images/reg-create-5.png)

    | Field | Description |
    |-------|-------------|
    | Forecast date feature | The column in the training dataset that contains date/time values used by DataRobot to detect the range of dates (the valid forecast range) available for use as the forecast point. |
    | Date/time format | The format used by the date/time features in the training dataset. |
    | Forecast point feature | The column in the training dataset that contains the point from which you are making a prediction. |
    | Forecast unit | The time unit (seconds, days, months, etc.) that comprise the [time step](glossary/index#time-step). |
    | Forecast distance feature | The column in the training dataset containing a unique time step—a relative position—within the forecast window. A time series model outputs one row for each forecast distance. |
    | Series identifier (optional, used for [multiseries models](multiseries)) | The column in the training dataset that identifies which series each row belongs to. |

    Finally, configure the registered model settings:

    | Field | Description |
    |-------|-------------|
    | Register model | Select one of the following:<ul><li>**Register new model:** Create a new registered model. This creates the first version (**V1**).</li><li>**Save as a new version to existing model:** Create a version of an existing registered model. This increments the version number and adds a new version to the registered model.</li></ul> |
    | Registered model name / Registered Model | Do one of the following:<ul><li>**Registered model name:** Enter a unique and descriptive name for the new registered model. If you choose a name that exists anywhere within your organization, the **Model registration failed** warning appears.</li><li>**Registered Model:** Select the existing registered model you want to add a new version to.</li></ul> |
    | Registered model version | Assigned automatically. This displays the expected version number of the version (e.g., V1, V2, V3) you create. This is always **V1** when you select **Register a new model**. |
    | **Optional settings**  | :~~: |
    | Version description | Describe the business problem these model packages solve, or, more generally, the relationship between them. |
    | Tags | Click **+ Add item** and enter a **Key** and a **Value** for each key-value pair you want to tag the model _version_ with. Tags do not apply to the registered model, just the versions within. Tags added when registering a new model are applied to **V1**. |

3. Once all fields for the external model are defined, click **Register**.

## Access registered models and versions

On the **Registered Models** page, you can sort registered models by **Name** or **Last modified**. In a registered model, on the **Versions** tab, you can sort versions by **Name**, **Created at**, **Last updated at**, or **Model type**:

![](images/sort-reg-models.png)

In the top-left corner of the **Registered Models** page, you can:

![](images/search-filter-reg-models.png)

* Click **Search** and enter the registered model name to locate it on the **Registered Models** page.

* Click **Filters** to enable, modify, or clear filters on the **Registered Models** page. You can filter by **Target name**, **Target type**, **Created by**, **Created between**, and **Modified between**. This control filters on registered models:

    ![](images/filter-reg-models.png)


## View model and version information

Once you locate the registered model or model version you are looking for, you can access a variety of information about the registered model or version.

### Model info

Click a registered model to open the details panel. From that panel, you can access the following tabs:

![](images/reg-model-info.png)

 Tab        | Description 
------------|------------
Versions    | View all model versions for a registered model and the associated creation and status information. <ul><li>To open the version in the current tab, click the row for the version you want to access.</li><li>To open the version in a new tab, click the open icon (![](images/icon-open.png)) next to the **Type** column for the version you want to access.</li></ul>
Deployments | View all model deployments for a registered model and the associated creation and status information. You can click a name in the **Deployment** column to open that deployment.
Model Info  | View the registered model **ID**, **Name**, **Latest Version**, **Created By** username, **Created** date, **Last Modified** date, **Target Type**, and **Target Name**. You can click the pencil icon (![](images/icon-pencil.png)) next to **Name** to edit the registered model's name.

### Version info

To open the registered model version, do either of the following:

![](images/reg-model-open-version.png)

* To open the version in the current tab, click the row for the version you want to access.

* To open the version in a new tab, click the open icon (![](images/icon-open.png)) next to the **Type** column for the version you want to access.

![](images/reg-model-ver-info.png)

!!! tip
    You can click **Switch** next to the name in the version header to select another version to view.

 Tab        | Description 
------------|------------
Info                     | View general model information for the model version. In addition: <ul><li>For all model types, you can click **+ Add tag** in the **Tags** field to apply additional tags to the version.</li><li>For DataRobot models, you can click the **Model Name** to open the model in the Leaderboard.</li><li>For custom models, you can click the **Custom Model ID** to open the model in the Custom Model Workshop.</li><li>For custom models [created via GitHub Actions](custom-model-github-action), you can click the **Git Commit Reference** to open the commit that created the model package in GitHub.</li>
Key Values               | Create [key values](model-registry-key-values) for the model version.
Compliance Documentation | Generate [compliance documentation](reg-compliance) for the model version.
Deployments              | View all model deployments for a registered model version, in addition to the associated creation and status information. You can click a name in the **Deployment** column to open that deployment.

## Deploy registered models

You can deploy a registered model at any time from the **Registered Models** page. To do that, you must open a custom model version:

1. On the **Registered Models** page, click the registered model containing the model version you want to deploy.

2. To open the registered model version, do either of the following:

    ![](images/reg-model-open-version.png)

    * To open the version in the current tab, click the row for the version you want to access.
    
    * To open the version in a new tab, click the open icon (![](images/icon-open.png)) next to the **Type** column for the version you want to access.

3. In the version header, click **Deploy**, and then [configure the deployment settings](add-deploy-info).

    ![](images/reg-model-ver-deploy.png)

## Manage registered models

You can **Share** or **Delete** registered models from the menu icon (![](images/icon-menu.png)) in the last column of the **Registered Models** page:

![](images/reg-model-menu.png)

!!! important "Changes to model sharing"
    With the introduction of the **Registered Models** page, _registered models_ are the model artifact used for sharing, not _model packages_. When you share a registered model, you automatically share each model package contained in that registered model.